
<h1><span class="yiyi-st" id="yiyi-14">numpy.polynomial.hermite.hermcompanion</span></h1>
        <blockquote>
        <p>原文：<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.polynomial.hermite.hermcompanion.html">https://docs.scipy.org/doc/numpy/reference/generated/numpy.polynomial.hermite.hermcompanion.html</a></p>
        <p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
        <p>校对：（虚位以待）</p>
        </blockquote>
    
<dl class="function">
<dt id="numpy.polynomial.hermite.hermcompanion"><span class="yiyi-st" id="yiyi-15"> <code class="descclassname">numpy.polynomial.hermite.</code><code class="descname">hermcompanion</code><span class="sig-paren">(</span><em>c</em><span class="sig-paren">)</span><a class="reference external" href="http://github.com/numpy/numpy/blob/v1.11.3/numpy/polynomial/hermite.py#L1569-L1611"><span class="viewcode-link">[source]</span></a></span></dt>
<dd><p><span class="yiyi-st" id="yiyi-16">返回c的缩放伴随矩阵。</span></p>
<p><span class="yiyi-st" id="yiyi-17">基底多项式被缩放，使得当<em class="xref py py-obj">c</em>是埃尔米特基本多项式时，伴随矩阵是对称的。</span><span class="yiyi-st" id="yiyi-18">这提供比未缩放的情况更好的特征值估计，并且对于基本多项式，如果使用<a class="reference internal" href="numpy.linalg.eigvalsh.html#numpy.linalg.eigvalsh" title="numpy.linalg.eigvalsh"><code class="xref py py-obj docutils literal"><span class="pre">numpy.linalg.eigvalsh</span></code></a>来获得它们，则特征值被保证为实数。</span></p>
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<tr class="field-odd field"><th class="field-name"><span class="yiyi-st" id="yiyi-19">参数：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-20"><strong>c</strong>：array_like</span></p>
<blockquote>
<div><p><span class="yiyi-st" id="yiyi-21">1  -  D数组从低到高排列的Hermite系数系数。</span></p>
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<tr class="field-even field"><th class="field-name"><span class="yiyi-st" id="yiyi-22">返回：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-23"><strong>mat</strong>：ndarray</span></p>
<blockquote class="last">
<div><p><span class="yiyi-st" id="yiyi-24">尺寸（deg，deg）的缩放伴随矩阵。</span></p>
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<p class="rubric"><span class="yiyi-st" id="yiyi-25">笔记</span></p>
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